AI 5G network management optimization
Prof. SCHEMBRA Giovanni
Orhestration and resource allocation will play a crucial role in management of the future 5G systems. In this context application of Artificial intelligence (AI) techniques will be challenging in optimizing performance and reducing energy consumption to enable new services, today unfeasible. Objective of the work is to define machine learning technique in a softwarized network environment realized with Linux Dockers and Containers managed with Kubernetes.
Study cycle:
undergraduate
Languages skills required:
English B1
Length:
2 months
Period:
second semester
Summer traineeships:
no
Research centre/company involved:
Università di Catania - Dipartimento di Ingegneria Elettrica, Elettronica e Informatica
Insurance:
Accident insurance during working hours only and Liability insurance
Position reserved for partner university within Erasmus bilateral traineeship agreement (specify the name of the university):
Laboratori DIEEI
Benefits:
none
Traineeship type:
non Erasmus placement
A.Y.:
2019-2020